Paper Info
Title
EEG-Based User Authentication in Multilevel Security Systems
Abstract
User authentication plays an important role in security systems. In general, there are three types of authentications: password based, token based, and biometrics based. Each of them has its own merits and drawbacks. Recently, the research communities successfully explore the possibility that electroencephalography EEG being as a new type of biometrics in person recognition, and hence the prospect of using EEG in user authentication is promising. An EEG-based user authentication system has the combined advantages of both password based and biometric based authentication systems, yet without their drawbacks. In this paper we propose to use EEG to authenticate users in multilevel security systems where users are asked to provide EEG signal for authentication by performing motor imagery tasks. These tasks can be single or combined, depending on the level of security required. The analysis and processing of EEG signals of motor imagery will be presented through our experimental results.
Year
DOI
Venue
2013
10.1007/978-3-642-53917-6_46
ADMA (2)
Keywords
Field
DocType
authentication,security,biometrics,eeg,pattern recognition,data mining
Data mining,Authentication,Computer science,Multilevel security,Artificial intelligence,Password,Biometrics,Security token,Multi-factor authentication,Electroencephalography,Machine learning,Motor imagery
Conference
Citations 
PageRank 
References 
4
0.45
11
Authors
5
Name
Order
Citations
PageRank
Tien Pham110714.49
Wanli Ma227032.72
Dat Tran345478.64
Phuoc Nguyen45813.29
Dinh Q. Phung51469144.58